We examine optimal managerial compensation and turnover policy in a principal-agent model in which the firm output is serially correlated over time. The model captures a learning-by-doing feature: higher effort by the manager increases the quality of the match between the firm and the manager in...

We examine collaboration in a one-arm bandit problem in which the players' actions affect the distribution over future payoffs. The players need to exert costly effort both to enhance the value of a risky technology and to learn about its current state. Both product value and learning are public...

There are legal grounds to hear competitors in merger control proceedings, and competitor involvement has gained significance. To what extent this is economically sensible is our question. The competition authority applies some welfare standard while the competitor cares about its own profit. In...

Does gender play a role in the context of team work? Our results based on a real-effort experiment suggest that performance depends on the composition of the team. We find that female and male performance differ most in mixed teams with revenue sharing between the team members, as men put in...

In illiquid markets, option traders may have an incentive to increase their portfolio value by using their impact on the dynamics of the underlying. We provide a mathematical framework within which to value derivatives under market impact in a multi-player framework by introducing strategic...

Does gender play a role in the context of team work? Our results based on areal-effort experiment suggest that performance depends on the composition of theteam. We find that female and male performance di¤er most in mixed teams withrevenue sharing between the team members, as men put in...

The Reversible Jump Markov Chain Monte Carlo (RJMCMC) method can enhance Bayesian DSGE estimation by sampling from a posterior distribution spanning potentially nonnested models with parameter spaces of different dimensionality. We use the method to jointly sample from an ARMA process of unknown...

We introduce a methodology for measuring default risk connectedness that is based on an out-of-sample variance decomposition of model forecast errors. The out-of-sample nature of the procedure leads to "realized" measures which, in practice, respond more quickly to crisis occurrences than those...

Motivated by the conjectured existence of trends in the intensity of tropical storms, this paper proposes new inferential methodology to detect a trend in the annual pattern of environmental data. The new methodology can be applied to data which can be represented as annual curves which evolve...

A growing literature uses changes in residual volatility for identifying structural shocks in vector autoregressive (VAR) analysis. A number of di erent models for heteroskedasticity or conditional heteroskedasticity are proposed and used in applications in this context. This study reviews the...